The document discusses Mike Daniel's talk on learning analytics and AI policy at the University of Michigan. It outlines how the university measures and uses student data through tools developed by its Digital Innovation Greenhouse (DIG) in accordance with its data sharing and institutional resource policies. It also describes how the university applies its learning analytics guiding principles of respect, transparency, accountability, empowerment, and continuous consideration to these tools, including by providing information about the principles and data use on its website and within each tool.

1. AIM Analytics - Learning
Analytics & Policy
Mike Daniel - Director, Policy & Operations
Office of Academic Innovation
November 20, 2017
@UMichiganAI

2. @UMichiganAI
Why are Learning Analytics important in AI?

3. @UMichiganAI
What do we measure?

4. @UMichiganAI
How to put data to work

5. @UMichiganAI
Data and the Future of Education

6. @UMichiganAI
How AI shares data & which policies apply
● MOOC Data Sharing Policy.
● Expansion into FERPA-protected student data through homegrown ed tech
software tools via AI’s Digital Innovation Greenhouse (DIG).
● Per the University’s Institutional Resource Management Policy (SPG 601.12), AI
has determined these tools contain two types of student data delineated under
the Policy that are stewarded by Chris Brooks as Data Manager: Student Class
Performance Management Data + Teaching and Learning Technology Usage.
● Forthcoming AI Data Policy which builds on framework in MOOC Data Sharing
Policy - Stay Tuned!

7. @UMichiganAI
How AI applies the Principles
● In concert with the creation of U-M’s Learning Analytics Guiding Principles (Respect,
Transparency, Accountability, Empowerment, and Continuous Consideration), AI
conducted a series of internal meetings related to DIG-supported tools around applying
these Principles.
● Outcome:
○ A forthcoming overview of the Guiding Principles on the AI Website including an Introduction, a definition
of learning analytics data, a breakdown of the Guiding Principles themselves, and a point of contact for
students if they have more questions about learning analytics and/or opting-out of research studies being
conducted through DIG tools.
○ Language that either has been or will be posted in each DIG-supported tool related to the Guiding
Principles and how the University uses student data collected in the tool.